Attention is a technique that mimics cognitive attention by either enhancing or diminishing parts of the input data to achieve improved performance. Attention in the context of neural networks has led to improved results across a variety of fields including natural language processing [1]}, image classification [2]}, image segmentation [3]}, and others due to its ability to dynamically model sequences. A field that will likely benefit greatly from the application of attention, is video action recognition. Current research has investigated using attention to attend across the frames of the video (temporal attention) and patches of the current image (spatial attention) [4]}, [5]}, [6]}. However, these methods attend only to visual features and do not utilize the motion between frames which is an important feature specific to videos.
